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48 articles matched your search for the keywords:
Science, Language, Demarcation, Micro-World, BACON, Chess

Concepts for an Agent-Based Framework for Interdisciplinary Social Science Simulation

Elke Mentges
Journal of Artificial Societies and Social Simulation 2 (2) 4

Kyeywords: Modelling Language, Software System, Multi-Agent System, Modelling Interactions, Toolkit

The Multi-Agent Modelling Language and the Model Design Interface

László Gulyás, Tamás Kozsik and John B. Corliss
Journal of Artificial Societies and Social Simulation 2 (3) 8

Kyeywords: Social Science Simulation, Agent-Based Modelling, Integrated Modelling Environment
Abstract: While computer models provide many advantages over traditional experimental methods, they also raise several problems. The process of software development is a complicated task with high potential for errors, especially when it is carried out by scientists holding their expertise in other fields than computer science. On the other hand, the process of creating computer simulations of social systems which reflect the reality of such systems requires insights considerably beyond expertise in computer science. The Multi-Agent Modelling Language (MAML) is one of the efforts to ease these difficulties. In its current version, MAML is a macro-language for Swarm (a freely distributed toolset under development at SFI), but it is also part of a larger Swarm-independent framework. Also, the design of MAML, while influenced by concepts from Swarm, is general enough to allow for later extension of the supported simulation kernels. This paper gives an overview of the mentioned larger framework, with special emphasis on MAML and its graphical CASE tool, the Model Design Interface.

Teaching Social Simulation with Matlab

Warren Thorngate
Journal of Artificial Societies and Social Simulation 3 (1) forum/1

Kyeywords: Simulation, Teaching, Social Processes, Programming Languages, Matlab
Abstract: Programming languages for social simulations are rapidly proliferating. The result is a Tower of Babel effect: Many of us find it increasingly effortful to learn and to teach more programming languages and increasingly difficult to sustain an audience beyond the programming dialect of our choice. We need a programming lingua franca. Here I argue why Matlab might be worth our consideration, especially to teach simulation programming techniques.

Some Strategies for the Simulation of Vocabulary Agreement in Multi-Agent Communities

Juan de Lara Jaramillo and Manuel Alfonseca
Journal of Artificial Societies and Social Simulation 3 (4) 2

Kyeywords: Multi-Agent Systems, Agent-Based Simulation, Self-Organization, Language
Abstract: In this paper, we present several experiments of belief propagation in multi-agent communities. Each agent in the simulation has an initial random vocabulary (4 words) corresponding to each possible movement (north, south, east and west). Agents move and communicate the associated word to the surrounding agents, which can be convinced by the 'speaking agent', and change their corresponding word by 'imitation'. Vocabulary uniformity is achieved, but strong interactions and competition can occur between dominant words. Several moving and trusting strategies as well as agent roles are analyzed.

"ArrierosAlife" a Multi-Agent Approach Simulating the Evolution of a Social System: Modeling the Emergence of Social Networks with "Ascape"

Klaus Auer and Timothy Norris
Journal of Artificial Societies and Social Simulation 4 (1) 6

Kyeywords: Cellular Automata, Multi-Agent Model, Evolution, Social Networks, Object Oriented Programming Language, Artificial Landscape
Abstract: The behavior of cellular automata is a very close representation of the evolution of complex social systems. We developed the simulation model "ArrierosAlife" to explore the behavior of changes in social networks over time. The model is based on empirical data, a result out of a longitudinal field work. The focus of this research is a comparison of network changes over time in the "real world" compared with the emergence of social networks in an artificial society. "Ascape" was used as a modeling frame work to facilitate the development and analysis of the simulation model. We will give a brief overview of the developed model and describe the experiences using "Ascape" as a framework.

UMDBS - a New Tool for Dynamic Microsimulation

Thomas Sauerbier
Journal of Artificial Societies and Social Simulation 5 (2) 5

Kyeywords: Microsimulation, Monte Carlo Simulation, Micro Data, Simulation Languages, Simulation Systems, UMDBS, MISTRAL
Abstract: Microsimulation is a powerful method for analysis and forecasting especially in the field of economics and social science. One of the main reasons for its relatively rare usage is that until now there has been no standard software available. The Universal Micro DataBase System, UMDBS, is a new tool that runs on any Windows PC. It is suited for all tasks involved in running a microsimulation starting from the import of external data, the development of the simulation model, to the analysis of the results. It includes MISTRAL, an integrated modelling language that allows implementing the simulation models as well as analysing the micro data. After a short introduction to microsimulation, this article first presents the UMDBS and its main functions. Then an overview to the new modelling language MISTRAL is given including the features, the structure, and the implementation. Finally information is given about how to get UMDBS for free.

SISTER: a Symbolic Interactionist Simulation of Trade and Emergent Roles

Deborah Duong and John Grefenstette
Journal of Artificial Societies and Social Simulation 8 (1) 1

Kyeywords: Agent-Based Model, Computational Social Theory, Economics Simulation, Symbolic Interactionism, Emergent Language, Sociological Roles
Abstract: SISTER, a Symbolic Interactionist Simulation of Trade and Emergent Roles, captures a fundamental social process by which macro level roles emerge from micro level symbolic interaction. The knowledge in a SISTER society is held culturally, suspended in the mutual expectations agents have of each other based on signs (tags) that they read and display. In this study, this knowledge includes how to create composite goods. The knowledge of coordinating their creation arises endogenously. A symbol system emerges to denote these tasks. In terms of information theory, the degree of mutual information between the agent\'s signs (tags) and their behavior increases over time. The SISTER society of this study is an economic simulation, in which agents have the choice of growing all the goods they need by themselves, or concentrating their efforts in making more of fewer goods and trading them for other goods. They induce the sign of an agent to trade with, while at the same time, they induce a sign to display. The signs come to mean sets of behaviors, or roles, through this double induction. A system of roles emerges, holding the knowledge of social coordination needed to distribute tasks among the agents.

Simulating the Emergence of New Religious Movements

M. Afzal Upal
Journal of Artificial Societies and Social Simulation 8 (1) 6

Kyeywords: Cognitive Science of Religion, Multiagent Systems, Rational Choice Theory, New Religious Movement Emergence
Abstract: Not unlike other social sciences, study of religion in general and study of new religious movements (NRMs) in particular, has suffered from a problem of having too many inter-related free variables and a few data points available to constrain their values. This paper suggests cognitively inspired computer modeling as a technique for exploring, refining and testing theories of religion. Although computer simulation has become a relatively accepted technique for studying social theories, it has rarely been used to study religion. To illustrate this point I describe in detail the Agent-based Information Entrepreneur Model (AIM), a computer model of the recently proposed cognitive theory of new religious movements.

Towards Good Social Science

Scott Moss and Bruce Edmonds
Journal of Artificial Societies and Social Simulation 8 (4) 13

Kyeywords: Methodology, Agent Based Social Simulation, Qualitative Analysis; Evidence; Conditions of Application; History of Science
Abstract: The paper investigates what is meant by "good science" and "bad science" and how these differ as between the natural (physical and biological) sciences on the one hand and social sciences on the other. We conclude on the basis of historical evidence that the natural science are much more heavily constrained by evidence and observation than by theory while the social sciences are constrained by prior theory and hardly at all by direct evidence. Current examples of the latter proposition are taken from recent issues of leading social science journals. We argue that agent based social simulations can be used as a tool to constrain the development of a new social science by direct (what economists dismiss as anecdotal) evidence and that to do so would make social science relevant to the understanding and influencing of social processes. We argue that such a development is both possible and desirable. We do not argue that it is likely.

The Logic of the Method of Agent-Based Simulation in the Social Sciences: Empirical and Intentional Adequacy of Computer Programs

Nuno David, Jaime Simão Sichman and Helder Coelho
Journal of Artificial Societies and Social Simulation 8 (4) 2

Kyeywords: Computer and Social Sciences, Agent-Based Simulation, Intentional Computation, Program Verification, Intentional Verification, Scientific Knowledge
Abstract: The classical theory of computation does not represent an adequate model of reality for simulation in the social sciences. The aim of this paper is to construct a methodological perspective that is able to conciliate the formal and empirical logic of program verification in computer science, with the interpretative and multiparadigmatic logic of the social sciences. We attempt to evaluate whether social simulation implies an additional perspective about the way one can understand the concepts of program and computation. We demonstrate that the logic of social simulation implies at least two distinct types of program verifications that reflect an epistemological distinction in the kind of knowledge one can have about programs. Computer programs seem to possess a causal capability (Fetzer, 1999) and an intentional capability that scientific theories seem not to possess. This distinction is associated with two types of program verification, which we call empirical and intentional verification. We demonstrate, by this means, that computational phenomena are also intentional phenomena, and that such is particularly manifest in agent-based social simulation. Ascertaining the credibility of results in social simulation requires a focus on the identification of a new category of knowledge we can have about computer programs. This knowledge should be considered an outcome of an experimental exercise, albeit not empirical, acquired within a context of limited consensus. The perspective of intentional computation seems to be the only one possible to reflect the multiparadigmatic character of social science in terms of agent-based computational social science. We contribute, additionally, to the clarification of several questions that are found in the methodological perspectives of the discipline, such as the computational nature, the logic of program scalability, and the multiparadigmatic character of agent-based simulation in the social sciences.

Multi-Agent Simulation of Emergence of Schwa Deletion Pattern in Hindi

Monojit Choudhury, Anupam Basu and Sudeshna Sarkar
Journal of Artificial Societies and Social Simulation 9 (2) 2

Kyeywords: Language Change, Linguistic Agent, Language Game, Multi-Agent Simulation, Schwa Deletion
Abstract: Recently, there has been a revival of interest in multi-agent simulation techniques for exploring the nature of language change. However, a lack of appropriate validation of simulation experiments against real language data often calls into question the general applicability of these methods in modeling realistic language change. We try to address this issue here by making an attempt to model the phenomenon of schwa deletion in Hindi through a multi-agent simulation framework. The pattern of Hindi schwa deletion and its diachronic nature are well studied, not only out of general linguistic inquiry, but also to facilitate Hindi grapheme-to-phoneme conversion, which is a preprocessing step to text-to-speech synthesis. We show that under certain conditions, the schwa deletion pattern observed in modern Hindi emerges in the system from an initial state of no deletion. The simulation framework described in this work can be extended to model other phonological changes as well.

Emerging Artificial Societies Through Learning

Nigel Gilbert, Matthijs den Besten, Akos Bontovics, Bart G.W. Craenen, Federico Divina, A.E. Eiben, Robert Griffioen, György Hévízi, Andras Lõrincz, Ben Paechter, Stephan Schuster, Martijn C. Schut, Christian Tzolov, Paul Vogt and Lu Yang
Journal of Artificial Societies and Social Simulation 9 (2) 9

Kyeywords: Artificial Societies, Evolution of Language, Decision Trees, Peer-To-Peer Networks, Social Learning
Abstract: The NewTies project is implementing a simulation in which societies of agents are expected to de-velop autonomously as a result of individual, population and social learning. These societies are expected to be able to solve environmental challenges by acting collectively. The challenges are in-tended to be analogous to those faced by early, simple, small-scale human societies. This report on work in progress outlines the major features of the system as it is currently conceived within the project, including the design of the agents, the environment, the mechanism for the evolution of language and the peer-to-peer infrastructure on which the simulation runs.

An "All Hands" Call to the Social Science Community: Establishing a Community Framework for Complexity Modeling Using Agent Based Models and Cyberinfrastructure

Lilian N. Alessa, Melinda Laituri and C. Michael Barton
Journal of Artificial Societies and Social Simulation 9 (4) 6

Kyeywords: Community-Based Complex Models, Mathematics, Social Sciences
Abstract: To date, many communities of practice (COP) in the social sciences have been struggling with how to deal with rapidly growing bodies of information. Many CoPs across broad disciplines have turned to community frameworks for complexity modeling (CFCMs) but this strategy has been slow to be discussed let alone adopted by the social sciences communities of practice (SS-CoPs). In this paper we urge the SS-CoPs that it is timely to develop and establish a CBCF for the social sciences for two major reasons: the rapid acquisition of data and the emergence of critical cybertools which can facilitate agent-based, spatially-explicit models. The goal of this paper is not to prescribe how a CFCM might be set up but to suggest of what components it might consist and what its advantages would be. Agent based models serve the establishment of a CFCM because they allow robust and diverse inputs and are amenable to output-driven modifications. In other words, as phenomena are resolved by a SS-CoP it is possible to adjust and refine ABMs (and their predictive ability) as a recursive and collective process. Existing and emerging cybertools such as computer networks, digital data collections and advances in programming languages mean the SS-CoP must now carefully consider committing the human organization to enabling a cyberinfrastructure tool. The combination of technologies with human interfaces can allow scenarios to be incorporated through 'if' 'then' rules and provide a powerful basis for addressing the dynamics of coupled and complex social ecological systems (cSESs). The need for social scientists to be more engaged participants in the growing challenges of characterizing chaotic, self-organizing social systems and predicting emergent patterns makes the application of ABMs timely. The enabling of a SS-CoP CFCM human-cyberinfrastructure represents an unprecedented opportunity to synthesize, compare and evaluate diverse sociological phenomena as a cohesive and recursive community-driven process.

Contra Epstein, Good Explanations Predict

Nicholas S. Thompson and Patrick Derr
Journal of Artificial Societies and Social Simulation 12 (1) 9

Kyeywords: ABM, Agent Based Model, Modeling, Prediction, Explanation, Philosophy of Science
Abstract: Epstein has argued that an explanation\'s capacity to make predictions should play a minor role in its evaluation . This view contradicts centuries of scientific practice and, at least, decades of philosophy of science. We argue that the view is not only unfounded but seems to arise from a mistaken fear that ABM models are in need of defense against the criticism that they don\'t necessarily forecast events in the natural or social world.

Forecasting a Language Shift Based on Cellular Automata

Francesc S. Beltran, Salvador Herrando, Doris Ferreres, Marc-Antoni Adell, Violant Estreder and Marcos Ruiz-Soler
Journal of Artificial Societies and Social Simulation 12 (3) 5

Kyeywords: Cellular Automata, Computational Simulations, Language, Social Dynamics
Abstract: Language extinction as a consequence of language shifts is a widespread social phenomenon that affects several million people all over the world today. An important task for social sciences research should therefore be to gain an understanding of language shifts, especially as a way of forecasting the extinction or survival of threatened languages, i.e., determining whether or not the subordinate language will survive in communities with a dominant and a subordinate language. In general, modeling is usually a very difficult task in the social sciences, particularly when it comes to forecasting the values of variables. However, the cellular automata theory can help us overcome this traditional difficulty. The purpose of this article is to investigate language shifts in the speech behavior of individuals using the methodology of the cellular automata theory. The findings on the dynamics of social impacts in the field of social psychology and the empirical data from language surveys on the use of Catalan in Valencia allowed us to define a cellular automaton and carry out a set of simulations using that automaton. The simulation results highlighted the key factors in the progression or reversal of a language shift and the use of these factors allowed us to forecast the future of a threatened language in a bilingual community.

The Development of Social Simulation as Reflected in the First Ten Years of JASSS: a Citation and Co-Citation Analysis

Matthias Meyer, Iris Lorscheid and Klaus G. Troitzsch
Journal of Artificial Societies and Social Simulation 12 (4) 12

Kyeywords: Citation Analysis, Co-Citation Analysis, Lines of Research, Multidisciplinary, Science Studies, Social Simulation
Abstract: Social simulation is often described as a multidisciplinary and fast-moving field. This can make it difficult to obtain an overview of the field both for contributing researchers and for outsiders who are interested in social simulation. The Journal for Artificial Societies and Social Simulation (JASSS) completing its tenth year provides a good opportunity to take stock of what happened over this time period. First, we use citation analysis to identify the most influential publications and to verify characteristics of social simulation such as its multidisciplinary nature. Then, we perform a co-citation analysis to visualize the intellectual structure of social simulation and its development. Overall, the analysis shows social simulation both in its early stage and during its first steps towards becoming a more differentiated discipline.

Agent-Based Models and Simulations in Economics and Social Sciences: From Conceptual Exploration to Distinct Ways of Experimenting

Denis Phan and Franck Varenne
Journal of Artificial Societies and Social Simulation 13 (1) 5

Kyeywords: Agent-Based Models and Simulations, Epistemology, Economics, Social Sciences, Conceptual Exploration, Model World, Credible World, Experiment, Denotational Hierarchy
Abstract: Now that complex Agent-Based Models and computer simulations spread over economics and social sciences - as in most sciences of complex systems -, epistemological puzzles (re)emerge. We introduce new epistemological concepts so as to show to what extent authors are right when they focus on some empirical, instrumental or conceptual significance of their model or simulation. By distinguishing between models and simulations, between types of models, between types of computer simulations and between types of empiricity obtained through a simulation, section 2 gives the possibility to understand more precisely - and then to justify - the diversity of the epistemological positions presented in section 1. Our final claim is that careful attention to the multiplicity of the denotational powers of symbols at stake in complex models and computer simulations is necessary to determine, in each case, their proper epistemic status and credibility.

A Methodology for Complex Social Simulations

Claudio Cioffi-Revilla
Journal of Artificial Societies and Social Simulation 13 (1) 7

Kyeywords: Agent-Based Modeling Methodology, M2M, Social Simulation, Computational Social Science, Social Complexity, Inner Asia
Abstract: Social simulation - an emerging field of computational social science - has progressed from simple toy models to increasingly realistic models of complex social systems, such as agent-based models where heterogeneous agents interact with changing natural or artificial environments. These larger, multidisciplinary projects require a scientific research methodology distinct from, say, simpler social simulations with more limited scope, intentionally minimal complexity, and typically under a single investigator. This paper proposes a methodology for complex social simulations - particularly inter- and multi-disciplinary socio-natural systems with multi-level architecture - based on a succession of models akin to but distinct from the late Imre Lakatos' notion of a 'research programme'. The proposed methodology is illustrated through examples from the Mason-Smithsonian project on agent-based models of the rise and fall of polities in Inner Asia. While the proposed methodology requires further development, so far it has proven valuable for advancing the scientific objectives of the project and avoiding some pitfalls.

Two Challenges in Simulating the Social Processes of Science

Edmund Chattoe-Brown
Journal of Artificial Societies and Social Simulation 14 (4) 1

Kyeywords: Simulating Science, Algorithmic Chemistry, Evolutionary Algorithms, Data Structures, Learning Systems
Abstract: This note discusses two challenges to simulating the social process of science. The first is developing an adequately rich representation of the underlying Data Generation Process which scientific progress can \"learn\". The second is how to get effective data on what, in broad terms, the properties of the \"future\" are. Paradoxically, with due care, we may learn a lot about the future by studying the past.

Science as a Social System and Virtual Research Environment

Sergey Parinov and Cameron Neylon
Journal of Artificial Societies and Social Simulation 14 (4) 10

Kyeywords: Virtual Research Environment, Science System Social Sustainability, Agent Based Modeling
Abstract: The accumulation of gradual changes in scientific landscape and research practice due to the Internet has the potential to enhance the quality of both cognitive and social aspects of science and scientists. New types of research outputs, modes of scientific communication and new circulation mechanisms, as well as enhanced opportunities for scientific re-use and measuring research impact, in combination with new approaches to research assessment and evaluation are all having profound effects on the social system of science. To be sure that these innovations will not break the social sustainability of the science community, it will be valuable to develop a model of science as a tool for computer simulation of social consequences from possible innovations within virtual research environment. Focusing on possible social problems related to these new virtual research environments this short paper provides a brief analysis of the current situation in science (challenges, problems, main actors), general views on model of science (landscape, main agents, important properties, etc.) and on areas where simulation can contribute to better understanding of possible futures for the scientific community.

A Social Process in Science and its Content in a Simulation Program

Wolfgang Balzer and Klaus Manhart
Journal of Artificial Societies and Social Simulation 14 (4) 11

Kyeywords: Social Simulation, Process, Science, Theory, Social Science, Philosophy of Science
Abstract: We lay open a position concerning the difference between scientific processes and processes in science. Not all processes in science are scientific. This leads into the center of social simulation. More scientific theories should be incorporated in social simulations, and this should lead to more united structural approaches.

Conference Models to Bridge Micro and Macro Studies of Science

Matthew Francisco, Staša Milojevic and Selma Šabanovic
Journal of Artificial Societies and Social Simulation 14 (4) 13

Kyeywords: Science of Science, Conferences, Community-Based Complex Models, Group Size, Methodology
Abstract: We propose using community-centered analyses and agent-based models of scientific gatherings such as conferences, symposia and workshops as a way to understand how scientific practices evolve and transition between local, community, and systems levels in science. We suggest using robotics as a case study of global, cross-cultural, interdisciplinary scientific practice. What is needed is a set of modeling frameworks for simulating both the internal and population dynamics of scientific gatherings. In this paper we make the case for conference models as a mid-level unit of analysis that can advance the ways scientists and citizens design systems for transferring and producing knowledge.

Simulating the Social Processes of Science

Bruce Edmonds, Nigel Gilbert, Petra Ahrweiler and Andrea Scharnhorst
Journal of Artificial Societies and Social Simulation 14 (4) 14

Kyeywords: Simulation, Science, Science and Technology Studies, Philosophy, Sociology, Social Processes
Abstract: Science is the result of a substantially social process. That is, science relies on many inter-personal processes, including: selection and communication of research findings, discussion of method, checking and judgement of others' research, development of norms of scientific behaviour, organisation of the application of specialist skills/tools, and the organisation of each field (e.g. allocation of funding). An isolated individual, however clever and well resourced, would not produce science as we know it today. Furthermore, science is full of the social phenomena that are observed elsewhere: fashions, concern with status and reputation, group-identification, collective judgements, social norms, competitive and defensive actions, to name a few. Science is centrally important to most societies in the world, not only in technical, military and economic ways, but also in the cultural impacts it has, providing ways of thinking about ourselves, our society and our environment. If we believe the following: simulation is a useful tool for understanding social phenomena, science is substantially a social phenomenon, and it is important to understand how science operates, then it follows that we should be attempting to build simulation models of the social aspects of science. This Special Section of <i>JASSS</i> presents a collection of position papers by philosophers, sociologists and others describing the features and issues the authors would like to see in social simulations of the many processes and aspects that we lump together as "science". It is intended that this collection will inform and motivate substantial simulation work as described in the last section of this introduction.

Computer Simulation and Emergent Reliability in Science

Kevin Zollman
Journal of Artificial Societies and Social Simulation 14 (4) 15

Kyeywords: Philosophy of Science, Sociology of Science, Computer Simulation
Abstract: While the popular image of scientists portrays them as objective, dispassionate observers of nature, actual scientists rarely are. It is not really known to what extent these individual departures from the scientific ideal effects the reliability of the scientific community. This paper suggests a number of concrete projects which help to determine this relationship.

Simulating What?

Harry Collins
Journal of Artificial Societies and Social Simulation 14 (4) 16

Kyeywords: Science, Language, Demarcation, Micro-World, BACON, Chess
Abstract: Any attempt to simulate science has first to say what science is. This involves asking three questions: 1) The Scope Question: What bit of science is the target? It is immensely confusing (as the history of these debates shows), if one simulates some little aspect of science, as in the case of BACON, and then claims that one has built a machine that can 'do science'. 2) The Micro-World Question: Is the criterion of success the reproduction of human science – with all the same findings turning up – or the simulation of something that is believed to be a scientific process with results that pertain only to the world of the simulation which do not correspond to the outcome of human science as we know it? If the latter it will be important to be sure that one is not merely developing a 'micro-world' – a world so tidied up for the purposes of simulation that it does not bear on human science. 3) The Chess Question: Even if the idea to reach the same results as has been reached by human science, does it have to be by 'the same' means in order to count as a simulation of human science? I call it the 'chess question' because Deep Blue does not play in the same way as human grand masters but is still better at winning.

Toward Multi-Level, Multi-Theoretical Model Portfolios for Scientific Enterprise Workforce Dynamics

Levent Yilmaz
Journal of Artificial Societies and Social Simulation 14 (4) 2

Kyeywords: Agent-Based Model, Complexity, Innovation, Science Studies, Diversity
Abstract: Development of theoretically sound methods and strategies for informed science and innovation policy analysis is critically important to each nation's ability to benefit from R&D investments. Gaining deeper insight into complex social processes that influence the growth and formation of scientific fields and development over time of a diverse workforce requires a systemic and holistic view. A research agenda for the development of rigorous complex adaptive systems models is examined to facilitate the study of incentives, strategies, mobility, and stability of the science-based innovation ecosystem, while examining implications for the sustainability of a diverse science enterprise.

Social Simulation That 'Peers into Peer Review'

Flaminio Squazzoni and Károly Takács
Journal of Artificial Societies and Social Simulation 14 (4) 3

Kyeywords: Peer Review, Social Simulation, Social Norms, Selection Biases, Science Policy
Abstract: This article suggests to view peer review as a social interaction problem and shows reasons for social simulators to investigate it. Although essential for science, peer review is largely understudied and current attempts to reform it are not supported by scientific evidence. We suggest that there is room for social simulation to fill this gap by spotlighting social mechanisms behind peer review at the microscope and understanding their implications for the science system. In particular, social simulation could help to understand why voluntary peer review works at all, explore the relevance of social sanctions and reputational motives to increase the commitment of agents involved, cast light on the economic cost of this institution for the science system and understand the influence of signals and social networks in determining biases in the reviewing process. Finally, social simulation could help to test policy scenarios to maximise the efficacy and efficiency of various peer review schemes under specific circumstances and for everyone involved.

Two Outline Models of Science: AMS And HAMS

Jim Doran
Journal of Artificial Societies and Social Simulation 14 (4) 5

Kyeywords: Computational Models of Science, Individual-Based Modelling, Scientific Method, Belief Systems, Belief Verification, Idealism
Abstract: Two abstract and computational models of the long-term process of science are proposed: AMS and HAMS. An outline specification of each model is given and the relationship between them explained. AMS takes an Olympian (\"artificial world\") view of science and its processes. HAMS is simpler and relatively more abstract and comprises only a small set of core processes. A first implementation of HAMS is described. How AMS and HAMS might be validated and used in experimental investigations is considered including problems that might arise. Further work is proposed. A brief coda concerns a related model of science formulated from an idealist rather than a materialist perspective.

Modeling Scientists as Agents. How Scientists Cope with the Challenges of the New Public Management of Science

Marc Mölders, Robin D. Fink and Johannes Weyer
Journal of Artificial Societies and Social Simulation 14 (4) 6

Kyeywords: Systems Theory, Theory of Action and Decision Making, Academic Publication System, Science System, New Public Management, Agent-Based Modeling and Simulation
Abstract: The paper at hand applies agent-based modeling and simulations (ABMS) as a tool to reconstruct and to analyze how the science system works. A Luhmannian systems perspective is combined with a model of decision making of individual actors. Additionally, changes in the socio-political context of science, such as the introduction of „new public management\", are considered as factors affecting the functionality of the system as well as the decisions of individual scientists (e.g. where to publish their papers). Computer simulation helps to understand the complex interplay of developments at the macro (system) and the micro (actor) level.

A Brief Survey of Some Relevant Philosophy of Science

Bruce Edmonds
Journal of Artificial Societies and Social Simulation 14 (4) 7

Kyeywords: Philosophy, Science, Simulation, Social Processes, Evolutionary Models, Sociology
Abstract: This briefly reviews some philosophy of science that might be relevant to simulating the social processes of science. It also includes a couple of examples from the sociology of science because these are inextricable from the philosophy.

Modelling Theory Communities in Science

Petra Ahrweiler
Journal of Artificial Societies and Social Simulation 14 (4) 8

Kyeywords: Simulating Science, Theory Interaction, Agent-Based Modelling, Theory Network
Abstract: This position paper presents a framework for modelling theory communities where theories interact as agents in a conceptual network. It starts with introducing the difficulties in integrating scientific theories by discussing some recent approaches, especially of structuralist theory of science. Theories might differ in reference, extension, scope, objectives, functions, architecture, language etc. To address these potential integration barriers, the paper employs a broad definition of "scientific theory", where a theory is a more or less complex description a describer puts forward in a context called science with the aim of making sense of the world. This definition opens up the agency dimension of theories: theories "do" something. They work on a - however ontologically interpreted - subject matter. They describe something, and most of them claim that their descriptions of this "something" are superior to those of others. For modelling purposes, the paper makes use of such description behaviour of scientific theories on two levels. The first is the level where theories describe the world in their terms. The second is a sub-case of the first: theories can of course describe the description behaviour of other theories concerning this world and compare with own description behaviour. From here, interaction and potential cooperation between theories could be potentially identified by each theory perspective individually. Generating inclusive theory communities and simulating their dynamics using an agent-based model means to implement theories as agents; to create an environment where the agents work as autonomous entities in a self-constituted universe of discourse; to observe what they do with this environment (they will try to apply their concepts, and instantiate their mechanisms of sense-making); and to let them mutually describe and analyse their behaviour and suggest areas for interaction. Some mechanisms for compatibility testing are discussed and the prototype of the model with preliminary applications is introduced.

For an Integrated Approach to Agent-Based Modeling of Science

Nicolas Payette
Journal of Artificial Societies and Social Simulation 14 (4) 9

Kyeywords: Agent-Based Models, Science Dynamics, Social Networks, Scientometrics, Evolutionary Computation
Abstract: The goal of this paper is to provide a sketch of what an agent-based model of the scientific process could be. It is argued that such a model should be constructed with normative claims in mind: i.e. that it should be useful for scientific policy making. In our tentative model, agents are researchers producing ideas that are points on an epistemic landscape. We are interested in our agents finding the best possible ideas. Our agents are interested in acquiring credit from their peers, which they can do by writing papers that are going to get cited by other scientists. They can also share their ideas with collaborators and students, which will help them eventually get cited. The model is designed to answer questions about the effect that different possible behaviors have on both the individual scientists and the scientific community as a whole.

Explanation in Agent-Based Modelling: Functions, Causality or Mechanisms?

Corinna Elsenbroich
Journal of Artificial Societies and Social Simulation 15 (3) 1

Kyeywords: Philosophy of Social Science, Causal Explanation, Functional Explanation, Mechanism Explanation, Analytic Sociology
Abstract: What kind of knowledge can we obtain from agent-based models? The claim that they help us to study the social world needs unpacking. I will defend agent-based modelling against a recent criticism that undermines its potential as a method to investigate underlying mechanisms and provide explanations of social phenomena. I show that the criticism is unwarranted and the problem can be resolved with an account of explanation that is associated with the social sciences anyway, the mechanism account of explanation developed in Machamer et al. (2000). I finish off discussing the mechanism account with relation to prediction in agent-based modelling.

Thomas C. Schelling and the Computer: Some Notes on Schelling's Essay &quot;On Letting a Computer Help with the Work&quot;

Rainer Hegselmann
Journal of Artificial Societies and Social Simulation 15 (4) 9

Kyeywords: Schelling Model, Segregation, Configuration Game, History of Computational Social Science, Agent Based Modeling
Abstract: Today the Schelling model is a standard component in introductory courses to agent-based modelling and simulation. When Schelling presented his model in the years between 1969 and 1978, his own analysis was based on manual table top exercises. Even more, Schelling explicitly warned against using computers for the analysis of his model. That is puzzling. A resolution to that puzzle can be found in an essay that Schelling wrote as teaching material for his students. That essay is now published by Schelling in JASSS, exactly 40 years after it was written. In his essay, Schelling gives a guided tour of a computer implementation of his model he himself implemented, de-spite his warnings. On this tour, though more in passing, Schelling gives hints to an extremely generalised version of his model. My article explains why we find the gen-eralised version of Schelling's model on the tour through his computer program rather than in his published articles.

MAIA: a Framework for Developing Agent-Based Social Simulations

Amineh Ghorbani, Pieter Bots, Virginia Dignum and Gerard Dijkema
Journal of Artificial Societies and Social Simulation 16 (2) 9

Kyeywords: Modelling Language, Model-Driven Engineering, Institutions, Social Simulation, Meta-Model
Abstract: In this paper we introduce and motivate a conceptualization framework for agent-based social simulation, MAIA: Modelling Agent systems based on Institutional Analysis. The MAIA framework is based on Ostrom's Institutional Analysis and Development framework, and provides an extensive set of modelling concepts that is rich enough to capture a large range of complex social phenomena. Developing advanced agent-based models requires substantial experience and knowledge of software development knowledge and skills. MAIA has been developed to help modellers who are unfamiliar with software development to conceptualize and implement agent-based models. It provides the foundation for a conceptualization procedure that guides modellers to adequately capture, analyse, and understand the domain of application, and helps them report explicitly on the motivations behind modelling choices. A web-based application supports conceptualization with MAIA, and outputs an XML file which is used to generate Java code for an executable simulation.

When Demography Met Social Simulation: A Tale of Two Modelling Approaches

Eric Silverman, Jakub Bijak, Jason Hilton, Viet Dung Cao and Jason Noble
Journal of Artificial Societies and Social Simulation 16 (4) 9

Kyeywords: Complexity Science, Demography, Health Care, Scenario Generation
Abstract: In this paper we present an agent-based model of a human population, designed to illustrate the potential synergies between demography and agent-based social simulation. In the modelling process, we take advantage of the perspectives of both disciplines: demography being more focused on matching statistical models to empirical data, and social simulation on explanations of social mechanisms underlying the observed phenomena. This work is based on earlier attempts to introduce agent-based modelling to demography, but extends them into a multi-level and multi-state framework. We illustrate our approach with a proof-of-concept model of partnership formation and changing health status over the life course. In addition to the agent-based component, the model includes empirical elements based on demographic data for the United Kingdom. As such, the model allows analysis of the demographic dynamics at a variety of levels, from the individual, through the household, to the whole population. We bolster this analysis further by using statistical emulation techniques, which allow for in-depth investigation of the interaction of model parameters and of the resulting output uncertainty. We argue that the approach \" although not fully predictive per se \" has four important advantages. First, the model is capable of studying the linked lives of simulated individuals in a variety of scenarios. Second, the simulations can be readily embedded in the relevant social or physical spaces. Third, the approach allows for overcoming some data-related limitations, augmenting the available statistical information with assumptions on behavioural rules. Fourth, statistical emulators enable exploration of the parameter space of the underlying agent-based models.

Computer-Based Global Models: From Early Experiences to Complex Systems

Rodrigo Castro and Pablo Jacovkis
Journal of Artificial Societies and Social Simulation 18 (1) 13

Kyeywords: Global Models, Social Processes, Complex Systems, History of Science, Computer Simulation, Latin American Modeling
Abstract: During the 1960s but mainly in the 1970s, large mathematical dynamic global models were implemented in computers to simulate the entire world, or large portions of it. Several different but interrelated subjects were considered simultaneously, and their variables evolved over time in an attempt to forecast the future, considering decades as time horizons. Global models continued to be developed while evidencing an increasing bias towards environmental aspects, or at least the public impact of models with such a focus became prevalent. In this paper we analyze the early evolution of computer-based global modeling and provide insights on less known pioneering works by South American modelers in the 1960s (Varsavsky and collaborators). We revisit relevant methodological aspects and discuss how they influenced different modeling endeavors. Finally, we overview how distinctive systemic approaches in global modeling evolved into the currently well-established discipline of complex systems.

Modelling Academics as Agents: An Implementation of an Agent-Based Strategic Publication Model

Xin Gu, Karen Blackmore, David Cornforth and Keith Nesbitt
Journal of Artificial Societies and Social Simulation 18 (2) 10

Kyeywords: Academic Science, Lotka’s Law, Strategic Publication Model, Agent-Based Model
Abstract: The rapid changes occurring in the higher education domain are placing increasing pressure on the actors in this space to focus efforts on identifying and adopting strategies for success. One particular group of interest are academics or scientists, and the ways that these individuals, or collectives as institutional or discipline-based science systems, make decisions about how best to achieve success in their chosen field. The agent-based model and simulation that we present draws on the hypothetical “strategic publication model” proposed by Mölders, Fink and Weyer (2011), and extends this work by defining experimental settings to implement a prototype ABMS in NetLogo. While considerable work remains to fully resolve theoretical issues relating to the scope, calibration and validation of the model, this work goes some way toward resolving some of the details associated with defining appropriate experimental settings. Also presented are the results of four experiments that focus on exploring the emergent effects of the system that result from varying the strategic mix of actors in the system.

Fill in the Gap: A New Alliance for Social and Natural Sciences

Tommaso Venturini, Pablo Jensen and Bruno Latour
Journal of Artificial Societies and Social Simulation 18 (2) 11

Kyeywords: Simulations, Big Data, Social Science, Micro Macro, Science Policy, Modeling
Abstract: In the last few years, electronic media brought a revolution in the traceability of social phenomena. As particles in a bubble chamber, social trajectories leave digital trails that can be analyzed to gain a deeper understanding of collective life. To make sense of these traces a renewed collaboration between social and natural scientists is needed. In this paper, we claim that current research strategies based on micro-macro models are unfit to unfold the complexity of collective existence and that the priority should instead be the development of new formal tools to exploit the richness of digital data.

"Anarchy" Reigns: A Quantitative Analysis of Agent-Based Modelling Publication Practices in JASSS, 2001-2012

Simon Angus and Behrooz Hassani-Mahmooei
Journal of Artificial Societies and Social Simulation 18 (4) 16

Kyeywords: Agent Based Modelling, Social Sciences, Simulation, Publishing
Abstract: Agent Based Modelling (ABM), a promising scientific toolset, has received criticism from some, in part, due to a claimed lack of scientific rigour, especially in the communication of its methods and results. To test the veracity of these claims, we conduct a structured analysis of over 900 scientific objects (figures, tables, or equations) that arose from 128 ABM papers published in the Journal of Artificial Societies and Social Simulation (JASSS), during the period 2001 to 2012 inclusive. Regrettably, we find considerable evidence in support of the detractors of ABM as a scientific enterprise: elementary plotting attributes are left off more often than not; basic information such as the number of replicates or the basis behind a particular statistic are not included; and few, if any, established methodological communication standards are apparent. In short, 'anarchy reigns'. Whilst the study was confined only to ABM papers of JASSS, we conclude that if the ABM community wishes its approach to be accepted further afield, authors, reviewers, and editors should take the results of our work as a wake-up call.

MERCURY: an Agent-Based Model of Tableware Trade in the Roman East

Tom Brughmans and Jeroen Poblome
Journal of Artificial Societies and Social Simulation 19 (1) 3

Kyeywords: Roman Economy, Network Science, Economics, Archaeology, Ceramics, History
Abstract: A large number of complex hypotheses exists that aim to explain aspects of the Roman economy, consisting of many explanatory factors that are argued to affect each other. Such complex hypotheses cannot be compared or tested through the traditional practice of qualitative argumentation and comparison with selected small sets of written and material sources alone. Moreover, these hypotheses often draw on different conceptual frameworks to abstract the same past phenomenon under study, hampering formal comparison. There is a need in the study of the Roman economy for more formal computational modelling for representing and comparing the many existing conceptual models, and for testing their ability to explain patterns observed in archaeological data where possible. This paper aims to address this need. It argues that communicating the potential contribution of computational modelling to scholars of the Roman economy should focus on providing theoretically well-founded arguments for the selection of the included and excluded variables, the conceptualisation used, and to address those elements of conceptual models that are at the forefront of scholarly debates. This approach is illustrated in this paper through MERCURY (Market Economy and Roman Ceramics Redistribution, after the Roman patron god of commerce), an agent-based model (ABM) of ceramic tableware trade in the Roman East. MERCURY presents a representation of two conflicting conceptual models of the degree of market integration in the Roman Empire, both of which serve as potential explanations for the empirically observed strong differences in the distribution patterns of tablewares. This paper illustrates how concepts derived from network science can be used to abstract both conceptual models, to implement these in an ABM and to formally compare them. The results of experiments with MERCURY suggest that limited degrees of market integration are unlikely to result in wide tableware distributions and strong differences between the tableware distributions. We conclude that in order for the discussion on the functioning of the Roman economy to progress, authors of conceptual models should (a) clearly define the concepts used and discuss exactly how these differ from the concepts used by others, (b) make explicit how these concepts can be represented as data, (c) describe the expected behaviour of the system using the defined concepts, (d) describe the expected data patterns resulting from this behaviour, and (d) define how (if at all) archaeological and historical sources can be used as reflections or proxies of these expected data patterns.

The Practice of Archiving Model Code of Agent-Based Models

Marco A. Janssen
Journal of Artificial Societies and Social Simulation 20 (1) 2

Kyeywords: Bibliometrics, Replication, Open Science, Computational Science
Abstract: To evaluate the concern over the reproducibility of computational science, we reviewed 2367 journal articles on agent-based models published between 1990 and 2014 and documented the public availability of source code. The percentage of publications that make the model code available is about 10%. The percentages are similar for publications that are reportedly dependent on public funding. There are big differences among journals in the public availability of model code and software used. This suggests that the varying social norms and practical convenience around sharing code may explain some of the differences among different sectors of the scientific community.

Utility, Impact, Fashion and Lobbying: An Agent-Based Model of the Funding and Epistemic Landscape of Research

Pawel Sobkowicz
Journal of Artificial Societies and Social Simulation 20 (2) 5

Kyeywords: Agent-Based Model, Epistemic Landscape, Research Funding, Fashions, Maps of Science
Abstract: The paper presents an agent-based model of an evolution of research interests in a scientific community. The research epistemic/funding landscape is divided into separate domains, which differ in impact on society and the perceived utility, which may determine the public willingness to fund. Scientific domains also differ in their potential for attention grabbing, crucial discoveries, which make them fashionable and also attract funding. The scientists may `follow' the availability of funds via a stylized grant based scheme. The model includes possible effects of the additional public relation and lobbying efforts, promoting certain disciplines at the cost of others. Results are based on two multi-parameter NetLogo models. The first uses an abstract, square lattice topology, and serves as a tool to understand the effects of the parameters describing the individual preferences. The second model, sharing the internal dynamics with the first one, is based on an actual research topics map and projects statistics, derived from the UK Research Council data for 2007--2016. Despite simplifications, results reproduce characteristics of the British research community surprisingly well.

Simulation for Interpretation: A Methodology for Growing Virtual Cultures

Ulf Lotzmann and Martin Neumann
Journal of Artificial Societies and Social Simulation 20 (3) 13

Kyeywords: Interpretative Research Process, Agent-Based Modelling, Generative Social Science, Qualitative Data, Thick Description, Cultural Studies
Abstract: Agent-based social simulation is well-known for generative explanations. Following the theory of thick description we extend the generative paradigm to interpretative research in cultural studies. Using the example of qualitative data about criminal culture, the paper describes a research process that facilitates interpretative research by growing virtual cultures. Relying on qualitative data for the development of agent rules, the research process combines several steps: Qualitative data analysis following the Grounded Theory paradigm enables concept identification, resulting in the development of a conceptual model of the concept relations. The software tool CCD is used in conceptual modelling which assists semi-automatic transformation in a simulation model developed in the simulation platform DRAMS. Both tools preserve traceability to the empirical evidence throughout the research process. Traceability enables interpretation of simulations by generating a narrative storyline of the simulation. Thereby simulation enables a qualitative exploration of textual data. The whole process generates a thick description of the subject of study, in our example criminal culture. The simulation is characterized by a socio-cognitive coupling of agents’ reasoning on the state of the mind of other agents. This reveals a thick description of how participants make sense of the phenomenology of a situation from the perspective of their worldview.

The Dynamics of Language Minorities: Evidence from an Agent-Based Model of Language Contact

Marco Civico
Journal of Artificial Societies and Social Simulation 22 (4) 3

Kyeywords: Language, Multilingualism, Minority, Complexity, Agent-Based Modelling, Population Dynamics
Abstract: This article discusses the adoption of a complexity theory approach to study the dynamics of language contact within multilingual communities. It develops an agent-based model that simulates the dynamics of communication within a community where a minority and a majority group coexist. The individual choice of language for communication is based on a number of simple rules derived from a review of the main literature on the topic of language contact. These rules are then combined with different variables, such as the rate of exogamy of the minority group and the presence of relevant education policies, to estimate the trends of assimilation of the minority group into the majority one. The model is validated using actually observed data from the case of Romansh speakers in the canton of Grisons, Switzerland. The data collected from the simulations are then analysed by means of regression techniques. This paper shows that macro-level language contact dynamics can be explained by relatively simple micro-level behavioural patterns and that intergenerational transmission is crucial for the long-term survival of minority-language groups.

Grade Language Heterogeneity in Simulation Models of Peer Review

Thomas Feliciani, Ramanathan Moorthy, Pablo Lucas and Kalpana Shankar
Journal of Artificial Societies and Social Simulation 23 (3) 8

Kyeywords: Peer Review, Grade Language, Agent-Based Modeling
Abstract: Simulation models have proven to be valuable tools for studying peer review processes. However, the effects of some of these models’ assumptions have not been tested, nor have these models been examined in comparative contexts. In this paper, we address two of these assumptions which go in tandem: (1) on the granularity of the evaluation scale, and (2) on the homogeneity of the grade language (i.e. whether reviewers interpret evaluation grades in the same fashion). We test the consequences of these assumptions by extending a well-known agent-based model of author and reviewer behaviour with discrete evaluation scales and reviewers’ interpretation of the grade language. In this way, we compare a peer review model with a homogeneous grade language, as assumed in most models of peer review, with a more psychologically realistic model where reviewers interpret the grades of the evaluation scale heterogeneously. We find that grade language heterogeneity can indeed affect the predictions of a model of peer review.

Natural-Language Multi-Agent Simulations of Argumentative Opinion Dynamics

Gregor Betz
Journal of Artificial Societies and Social Simulation 25 (1) 2

Kyeywords: Opinion Dynamics, Argumentation, Natural Language Processing, Language Model
Abstract: This paper develops a natural-language agent-based model of argumentation (ABMA). Its artificial deliberative agents (ADAs) are constructed with the help of so-called neural language models recently developed in AI and computational linguistics. ADAs are equipped with a minimalist belief system and may generate and submit novel contributions to a conversation. The natural-language ABMA allows us to simulate collective deliberation in English, i.e. with arguments, reasons, and claims themselves — rather than with their mathematical representations (as in symbolic models). This paper uses the natural-language ABMA to test the robustness of symbolic reason-balancing models of argumentation (Mäs & Flache 2013; Singer et al. 2019): First of all, as long as ADAs remain passive, confirmation bias and homophily updating trigger polarization, which is consistent with results from symbolic models. However, once ADAs start to actively generate new contributions, the evolution of a conversation is dominated by properties of the agents as authors. This suggests that the creation of new arguments, reasons, and claims critically affects a conversation and is of pivotal importance for understanding the dynamics of collective deliberation. The paper closes by pointing out further fruitful applications of the model and challenges for future research.

The Ethics of Agent-Based Social Simulation

David Anzola, Pete Barbrook-Johnson and Nigel Gilbert
Journal of Artificial Societies and Social Simulation 25 (4) 1

Kyeywords: Agent-Based Modelling, Research Ethics, Ethical Standards, Responsible Science, Scientific Integrity, Code of Ethics
Abstract: The academic study and the applied use of agent-based modelling of social processes has matured considerably over the last thirty years. The time is now right to engage seriously with the ethics and responsible practice of agent-based social simulation. In this paper, we first outline the many reasons why it is appropriate to explore an ethics of agent-based modelling and how ethical issues arise in its practice and organisation. We go on to discuss different approaches to standardisation as a way of supporting responsible practice. Some of the main conclusions are organised as provisions in a draft code of ethics. We intend for this draft to be further developed by the community before being adopted by individuals and groups within the field informally or formally